# ML CLI

Fast CLI tool for managing ML experiments.

## Quick Start

```bash
# 1. Build
zig build

# 2. Setup configuration
./zig-out/bin/ml init

# 3. Run experiment
./zig-out/bin/ml sync ./my-experiment --queue
```

## Commands

- `ml init` - Setup configuration
- `ml sync <path>` - Sync project to server  
- `ml queue <job1> [job2 ...] [--commit <id>] [--priority N]` - Queue one or more jobs
- `ml status` - Check system/queue status for your API key
- `ml monitor` - Launch monitoring interface (TUI)
- `ml cancel <job>` - Cancel a running/queued job you own
- `ml prune --keep N` - Keep N recent experiments
- `ml watch <path>` - Auto-sync directory
- `ml experiment log|show|list|delete` - Manage experiments and metrics

### Experiment workflow (minimal)

- `ml sync ./my-experiment --queue`  
  Syncs files, computes a unique commit ID for the directory, and queues a job.

- `ml queue my-job`  
  Queues a job named `my-job`. If `--commit` is omitted, the CLI generates a random commit ID
  and records `(job_name, commit_id)` in `~/.ml/history.log` so you don't have to remember hashes.

- `ml experiment list`  
  Shows recent experiments from history with alias (job name) and commit ID.

- `ml experiment delete <alias|commit>`  
  Cancels a running/queued experiment by job name, full commit ID, or short commit prefix.

## Configuration

Create `~/.ml/config.toml`:

```toml
worker_host = "worker.local"
worker_user = "mluser" 
worker_base = "/data/ml-experiments"
worker_port = 22
api_key = "your-api-key"
```

## Install

```bash
# Install to system
make install

# Or copy binary manually
cp zig-out/bin/ml /usr/local/bin/
```

## Need Help?

- `ml --help` - Show command help
- `ml <command> --help` - Show command-specific help